Nav Mathur is Senior Director of Global Solutions at Neo4j. He is responsible for solutions development and go-to-market activities.
Data is both our most valuable asset and our biggest ongoing challenge. As data grows in volume, variety and complexity, across applications, clouds and siloed systems, traditional ways of working with data no longer work. Increasingly, businesses are recognizing a need to harness all of their... read more
Data is both our most valuable asset and our biggest ongoing challenge. As data grows in volume, variety and complexity, across applications, clouds and siloed systems, traditional ways of working with data no longer work. Increasingly, businesses are recognizing a need to harness all of... read more
Data is both our most valuable asset and our biggest ongoing challenge. As data grows in volume, variety and complexity, across applications, clouds and siloed systems, traditional ways of working with data no longer work. Increasingly, businesses are recognizing a need to harness all of their... read more
Data is both our most valuable asset and our biggest ongoing challenge. As data grows in volume, variety and complexity, across applications, clouds and siloed systems, traditional ways of working with data no longer work. Increasingly, businesses are recognizing a need to harness all of their... read more
Data is both our most valuable asset and our biggest ongoing challenge. As data grows in volume, variety and complexity, across applications, clouds and siloed systems, traditional ways of working with data no longer work. Increasingly, businesses are recognizing a need to harness all of their... read more
Recommendation engines have become a crucial component of modern applications of all types. This core need has triggered a shift from relational and big-data approaches to graph-based technologies that are purpose-built to handle the rigorous demands of real-time recommendations. This week, in... read more
Recommendation engines have become a crucial component of modern applications of all types. This core need has triggered a shift from relational and big-data approaches to graph-based technologies that are purpose-built to handle the rigorous demands of real-time recommendations. This week, in... read more
Recommendation engines have become a crucial component of modern applications of all types. This core need has triggered a shift from relational and big-data approaches to graph-based technologies that are purpose-built to handle the rigorous demands of real-time recommendations. This week, in... read more
Recommendation engines have become a crucial component of modern sales, finance, logistics and human resources applications. This core need has triggered a shift from relational and big-data approaches to graph-based technologies that are purpose-built to handle the rigorous demands of real-time... read more
Recommendation engines have become a crucial component of modern sales, finance, logistics and human resources applications. This core need has triggered a shift from relational and big-data approaches to graph-based technologies that are purpose-built to handle the rigorous demands of real-time... read more
Money launderers get smarter every day, which means organizations need the right tools to stay one step ahead of these nefarious parties. Graph technology helps you follow the money trail, identifying and tracking circular money transactions to get to the source of fraud. This infographic... read more
The new California Consumer Privacy Act (CCPA) takes effect at the beginning of 2020 and imposes stiff penalties on those that misuse and resell consumers’ private information. Nevada and New York have also introduced their own privacy regulations. Canada and Mexico, as well as Texas,... read more
The new California Consumer Privacy Act (CCPA) takes effect at the beginning of 2020 and imposes stiff penalties on those that misuse and resell consumers’ private information. Nevada and New York have also introduced their own privacy regulations. Canada and Mexico, as well as Texas,... read more
The new California Consumer Privacy Act (CCPA) takes effect at the beginning of 2020 and imposes stiff penalties on those that misuse and resell consumers’ private information. Nevada and New York have also introduced their own privacy regulations. Canada and Mexico, as well as Texas,... read more
Predictive systems, like recommendation systems, have become an extremely important source of new revenue growth and have proven to improve user stickiness. Because of their direct impact on top-line revenue through the organic use of enterprise data, recommendation systems are being... read more
Financial regulations in the U.S. has become a complicated and fragmented system, but why? Various authorities creating compliance laws include a cast of six federal regulating agencies: The Federal Reserve, Office of the Comptroller of the Currency, the National Credit Union Administration, the... read more
Having a lot of data to mine from is a truly beautiful thing. But many businesses today struggle with data – especially as it grows and becomes more complex – that's stored in different data repositories, not to mention different formats and permissions. Typical types of disconnected data... read more
"You may also like" sounds simple, but there's a lot happening behind the scenes. Real-time recommendations work best when they take into account both the user's needs (what is of interest to them) and your business strategy (items you need to promote). The truly amazing thing is how... read more
In this series on the FRTB, we delved into what is required for effective internal risk models using a graph database like Neo4j. In previous weeks, we looked at the requirements of FRTB compliance and the relationship between risk modeling and data lineage. Last week, we explained why modern... read more
Relational database technology can't handle what is coming in banking and risk modeling. By the 2020s, Accenture predicts current banking business models will be swept away by a tide of ever-evolving technology and other rapidly occurring changes. The right foundation for building compliance... read more
Where did the data come from, originally? That’s a key question that the Fundamental Review of the Trading Book (FRTB) rules will require banks to answer in real-time. Banks must be able to decompose risk models to uncover the full lineage of investment data. Think of it as Ancestry.com for... read more
Sweeping regulations are changing the way banks handle risk. The Fundamental Review of the Trading Book (FRTB) represents an important shift designed to provide a firm foundation for the future. While laws passed after the financial crisis offered a patchwork, the FRTB is a change that offers banks... read more
How do you prevent another global financial crisis like the one in 2008? The answer lies in better visibility into the deep connections in risk data. Armed with an understanding of risk data lineage, financial houses could have limited their exposure. A connected data foundation not only... read more
Regulations, such as BCBS 239, are driving banks to reexamine the way they manage financial risk management data. Building a connected data foundation supports a world of innovative uses of your enterprise data – including 360-degree visibility of your customers, detecting and preventing... read more
As governmental regulations tighten, today’s banks must have a thorough and systematic understanding of risk calculations and their associated data lineage – including where underlying data originates and how it flows through enterprise systems. Forward-looking banks are uniting data silos... read more